Social network for merchants

ABSTRACT

A social network for merchants is described. A payment processing service can receive first merchant information associated with characteristic(s) of a first merchant and second merchant information associated with characteristic(s) of a second merchant. The payment processing service can determine a similarity between the first merchant and the second merchant based on analyzing the first merchant information and the second merchant information with a data model. Based at least in part on the similarity, the payment processing service can associate the first merchant and the second merchant with a merchant group and enable the first merchant and the second merchant to access a service associated with a merchant social network based at least in part on the association with the merchant group.

PRIORITY

This application is a continuation of, and claims priority to, U.S.patent application Ser. No. 15/885,716, filed on Jan. 31, 2018, and isfully incorporated by reference herein.

BACKGROUND

A merchant that is seeking assistance or advice for its business canvisit a support website of a payment processing service whose servicesthe merchant uses. At the support website, the merchant can browse orsearch posts by other merchants for relevant information. However, whilethe support website can provide a great deal of information, theinformation is not specific to the particular merchant that is seekingassistance. Additionally, if the merchant obtains information from thesupport website, the merchant has no way of knowing whether theinformation is credible.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is set forth with reference to the accompanyingfigures. In the figures, the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Theuse of the same reference numbers in different figures indicates similaror identical items or features.

FIG. 1 illustrates an example process of forming and using a socialnetwork for merchants according to some implementations.

FIG. 2 illustrates an example environment for a social network formerchants according to some implementations.

FIG. 3 is a flow diagram illustrating an example process for training adata model to determine similarity between one or more merchantsaccording to some implementations.

FIG. 4 is a flow diagram illustrating an example process for groupingsimilar merchants to enable access to merchant social network servicesaccording to some implementations.

FIG. 5 is a flow diagram illustrating an example process forfacilitating merchant communications via a social network for merchantsaccording to some implementations.

FIG. 6 is a flow diagram illustrating an example process for determininga recommended merchant recipient to answer a merchant inquiry accordingto some implementations.

DETAILED DESCRIPTION

Techniques described herein are directed to a social network formerchants. For the purpose of this discussion, a merchant can be anyentity that offers items (e.g., goods or services) for sale. In at leastone example, a merchant can utilize a payment processing service thatprocesses payments on behalf of the merchant. In at least one example,the payment processing service can additionally and/or alternativelyprovide payroll services, inventory management services, employeemanagement services, financing services, appointment services, etc. formerchants. In at least one example, a merchant can desire to interactwith other merchants associated with the payment processing serviceand/or agents of the payment processing service (e.g., support agents).Techniques described herein are directed to grouping merchants to enablemerchants to interact with other similar merchants. Such grouping canenable merchants to access credible and/or relevant information fromother similar merchants.

As described above, merchants who seek assistance or advice can visitsupport websites, which can include a page for merchants to ask and/oranswer questions, post helpful tips, etc. However, the informationposted to such pages is not specific to any particular merchant ormerchant characteristic. For example, a merchant seeking informationcannot determine whether a post or comment on a page was posted by amerchant that is nearby (if proximity is desired), or by a merchant thatis in a similar business (if a merchant in a similar business isdesired), or that a post is by a merchant at all. Thus, the merchantlacks reassurance that the information on the page can be trusted.Furthermore, existing techniques for connecting merchants have variouslimitations. For example, existing techniques for connecting merchantsdo not enable merchants to directly question (only) similar merchants(who share at least one characteristic) and, instead, require merchantsto post questions that are accessible to any (unreliable or dissimilar)person or entity using the website. Techniques described herein providea social network for merchants to enable merchants at least to exchangeinformation with confidence of its relevance and/or credibility.

Techniques described herein are directed to the formation andutilization of merchant groups. In one example, merchant groups enablemerchants to exchange information with other similar merchants. For thepurpose of this discussion, a merchant group can refer to two or moremerchants with a determined similarity that meets or exceeds athreshold. In at least one example, two merchants having at least oneshared characteristic can have a determined similarity that meets orexceeds a threshold. The merchant groups enable merchants to receiverelevant and credible information from other merchants in a samemerchant group, and access additional social networking services asdescribed herein. For instance, merchants in a merchant group can use awebsite, application, or other technology to communicate with each otherby posting or sharing information, comments, messages, images,resources, etc. As a non-limiting example, a merchant with a questioncan post the question to a message board that restricts access tomerchants in a particular merchant group (who are therefore similar tothe merchant in at least one way). As a result, the merchant can beconfident that responses received via the message board are relevantand/or credible.

The merchant social network described herein can facilitate theprovisioning of accurate, credible, and/or relevant information tomerchants. Furthermore, the merchant social network described herein canfacilitate merchant trust in the information received via an assignedmerchant group. That is, merchants in a merchant group can haveconfidence that information received via the merchant group is relevantand/or credible. For instance, in a non-limiting example, a floristassociated with a particular merchant group who is seeking informationregarding suppliers can request and/or receive information from otherflorists. By seeking information from florists in a specific floristmerchant group, this merchant can have confidence that the informationis relevant and/or credible. As another example, a non-profitcorporation can seek and receive information regarding payroll fromother non-profit corporations that are members of a non-profitcorporations merchant group. The merchant seeking information can relyon the fact that the group consists of non-profit corporations indetermining the relevancy and/or credibility of the information.

Each merchant serviced by the payment processing service can beassociated with a plurality of characteristics. Characteristics ofmerchants can include, but are not limited to, characteristics specificto a merchant itself, for example, a type of merchant, a merchantcategory code (“MCC”), a location(s) of a merchant, hours of operationof a merchant, non-profit or for-profit status of a merchant, mobilityof a merchant store (e.g., whether the merchant operates from a foodtruck or a building), inventory of a merchant, square footage of abrick-and-mortar store of a merchant, items offered for sale by amerchant, etc. Furthermore, characteristics of merchants can alsoinclude, but are not limited to, characteristics associated withmerchant transactions, which can include, for example, a volume oftransactions processed by a merchant (or on behalf of the merchant), afrequency of transactions processed by a merchant (or on behalf of themerchant), an average transaction amount for transactions processed by amerchant (or on behalf of the merchant), a transaction amount fortransactions occurring during a period of time that are processed by amerchant (or on behalf of the merchant), an average transaction amountfor transactions occurring during a period of time that are processed bya merchant (or on behalf of the merchant), most popular time(s) of dayfor transactions processed by a merchant (or on behalf of the merchant),a payment history associated with a merchant, etc. Moreover,characteristics of merchants may also include, but are not limited to,characteristics associated with various entities associated with amerchant, which can include, for example, suppliers used by a merchant,customers of a merchant, merchants related to a merchant (e.g., throughcommon ownership), a number or identity of employees of a merchant, etc.In at least one example, characteristics of merchants can also include,but are not limited to, characteristics associated with a relationshipbetween a merchant and payment processing service, which can include,for example, a type of point-of-sale (“POS”) device used by a merchant,payment processing service services used by a merchant (e.g., invoiceservices, appointment services, POS services, e-commerce services),support requests, etc.

Techniques described herein can associate merchants having one or moreshared characteristics with a same merchant group. That is, in at leastone example, merchants having a similarity above a threshold can beassociated with a same merchant group. For example, a merchant group caninclude merchants with a shared location and/or a shared MCC. In someexamples, a merchant can be associated with more than one merchantgroup. As a non-limiting example, a florist who is located in a 21271ZIP code could be a member of the “Location 21271” merchant group inaddition to being a member of the “Florist” merchant group. Techniquesdescribed herein can associate merchants with merchant groups uponinitial registration with the payment processing service, or at any timeduring which merchants utilize services of the payment processingservice. For instance, upon initial registration with the paymentprocessing service, the payment processing service can associate amerchant with one or more merchant groups that are associated with oneor more characteristics of the merchant. In some examples, the paymentprocessing service can make such an association based on an election bythe merchant, or, in other examples, without an election by the merchant(e.g., automatically).

In at least one example, the number and/or size of merchant groups canbe determined at least in part by the number of merchants and/or thenumber of characteristics associated with merchants. Furthermore,merchant groups and merchant group membership can be dynamic, such thatthe number of merchant groups and/or the membership of such merchantgroups changes depending on changing numbers of merchants and/orchanging characteristics of the merchants. As the number of merchantsincreases, so, too, does the personalization of the merchant socialnetwork for each merchant. For instance, as more merchants join themerchant social network described herein, additional and/or alternativemerchant groups can be formed, which can increase the specificity of howmerchants are grouped. That is, as more merchants join the merchantsocial network, the similarity between merchants within a merchant groupcan increase, thereby enhancing the relevance and personalization ofinteractions between merchants in a same merchant group.

Techniques described herein can provide a number of benefits andimprovements for both merchants and the payment processing service. Asdescribed above, techniques described herein enable merchants to accessrelevant and/or credible information. That is, by grouping merchantsbased on similarity and enabling grouped merchants to exchangeinformation, techniques described herein enable merchants to have moretrust in the information they are receiving.

Furthermore, an additional technical benefit provided by the techniquesdescribed herein is a reduced burden on the payment processing servicesupport team. For example, when associated with a merchant group asdescribed herein, a merchant can find a solution to a problem, concern,issue, etc. by searching within resources of the merchant group ratherthan by requesting assistance from the support team. Furthermore, thesystem utilizes machine learning models to group similarly-situatedmerchants together and can automatically provision communicationchannels between merchants and associated devices within a merchantgroup in order to respond to identified problems or inquiries. Moreover,when an inquiry is directed to the support team, the support team itselfcan use the merchant social network to more quickly and accuratelyidentify solutions. For example, the support team can focus a search onrecords of past problems of merchants who are similar to the merchantseeking support (that is, who are in a same merchant group). Forinstance, as a non-limiting example, if a merchant is experiencingdifficulty with a POS device, the support team can (1) determine thatthe merchant seeking assistance is a baker, (2) search support ticketsof a “Baker” merchant group, and (3) determine that a particular ovenused in bakeries has been found to cause interference with POS deviceswhen the POS devices were within 10 feet of the oven. The merchantsocial network system or the support team can therefore more quicklytroubleshoot the merchant's problem by use of the merchant groups.

Additionally, techniques described herein can provide variouscomputational benefits, which can increase the efficiency with whichmerchants are able to exchange information. For instance, a merchantsocial network, as described herein, reduces the burden on server(s)associated with the payment processing service: For example, techniquesdescribed herein enable reductions to storage, processing, and otherresources that are required at server(s). The reduced burden on theserver(s) stems, at least in part, from the fact that merchants can moreeffectively find solutions within the merchants' respective merchantgroups than by using payment processing service resources that do notpartition merchant communications by merchant characteristic(s). Theresulting increased efficiency in identifying solutions facilitated bymerchant groups obviates or lessens the number of searches, posts,comments, messages, etc. by merchants to the payment processing service.As such, techniques described herein both increase merchant confidencein information received and reduce computational burdens on server(s)facilitating such information exchange.

FIG. 1 illustrates an example environment 100 for forming and usingmerchant groups according to some implementations. Environment 100includes two merchants who use services of payment processing service102: merchant A 104A and merchant B 104B (collectively, merchants 104).Two merchants 104 are shown for ease of illustration; however,environment 100 can include any number of merchants. Each merchant A104A, 104B can operate a merchant device. For instance, merchant A 104Acan operate merchant device 106A, and merchant B 104B can operatemerchant device 106B (collectively, merchant devices 106). Each merchantdevice 106A, 106B can be associated with a user interface (UI) foraccessing the merchant social network. For instance, merchant device106A can include UI 108A for social network access and merchant device106B can include UI 108B for social network access (collectively, UIs108).

In some examples, UI 108A for social network access can be presented viaa web browser, or the like, that enables merchant A 104A to access andmanage services of the merchant social network. In other examples, UI108A for social network access can be presented via an application, suchas a mobile application or desktop application, which can be provided bypayment processing service 102, or which can be an otherwise dedicatedapplication. Similarly, UI 108B for social network access can bepresented via a web browser, an application, etc.

In at least one example, payment processing service 102 can providevarious services, such as, but not limited to payment processingservices, payroll services, inventory management services, employeemanagement services, financing services, and appointment services. Oneor more computing devices can perform one or more actions on behalf ofpayment processing service 102, as described below with reference toFIG. 2 . In at least one example, payment processing service 102 canreceive merchant information 110 from one or more information sourcesand/or systems 112. In additional and/or alternative examples, paymentprocessing service 102 can determine merchant information 110 based atleast partly on merchant information 110 received from one or moreinformation sources and/or systems 112. In at least one example,merchant A 104A can be associated with merchant A information 110A andmerchant B 104B can be associated with merchant B information 110B.

For the purpose of this discussion, merchant information 110 can includeinformation associated with a merchant. For the purpose of thisdiscussion, one or more characteristics, as described above and below,can be determined based on merchant information 110. That is, merchantinformation 110 associated with a merchant can include a plurality ofcharacteristics associated with the merchant and/or can be used todetermine merchant characteristic information.

For instance, merchant information 110 can correspond to merchantcharacteristics that can include, but are not limited to characteristicsspecific to a merchant itself, for example, a type of merchant, amerchant category code (“MCC”), a location(s) of a merchant, hours ofoperation of a merchant, non-profit or for-profit status of a merchant,mobility of a merchant store (e.g., whether the merchant operates from afood truck or a building), inventory of a merchant, square footage of abrick-and-mortar store of a merchant, items offered for sale by amerchant, etc. Furthermore, characteristics of merchants can alsoinclude, but are not limited to, characteristics associated withmerchant transactions, which can include, for example, a volume oftransactions processed by a merchant (or on behalf of the merchant), afrequency of transactions processed by a merchant (or on behalf of themerchant), an average transaction amount for transactions processed by amerchant (or on behalf of the merchant), a transaction amount fortransactions occurring during a period of time that are processed by amerchant (or on behalf of the merchant), an average transaction amountfor transactions occurring during a period of time that are processed bya merchant (or on behalf of the merchant), most popular time(s) of dayfor transactions processed by a merchant (or on behalf of the merchant),a payment history associated with a merchant, etc. Moreover,characteristics of merchants can also include, but are not limited to,characteristics associated with various entities associated with amerchant, which can include, for example, suppliers used by a merchant,customers of a merchant, merchants related to a merchant (e.g., throughcommon ownership), a number or identity of employees of a merchant, etc.In at least one example, characteristics of merchants can also include,but are not limited to, characteristics associated with a relationshipbetween a merchant and payment processing service, which can include,for example, a type of POS device used by a merchant, payment processingservice services used by a merchant (e.g., invoice services, appointmentservices, POS services, e-commerce services), support requests, etc.Additional and/or alternative merchant information 110 can be imagined.

As described above, merchant information 110 can be received by and/ordetermined by payment processing service 102. In at least one example,payment processing service 102 can receive merchant information 110 fromone or more information sources and/or systems 112. Information sourcesand/or systems 112 can include merchant device(s) (e.g., merchant device106A, merchant device 106B, etc.), social media platforms (e.g.,FACEBOOK®, LINKEDIN®, etc.), review platforms (e.g., YELP®, etc.), callsand/or messages received in association with support requests, etc.

Payment processing service 102 can train and store data model(s) 114. Inat least one example, payment processing service 102 can utilize machinelearning algorithms to build, modify, or otherwise utilize data model(s)114. In at least one example, the algorithms can include memory-basedcollaborative filtering algorithms, model-based collaborative filteringalgorithms, feature-based similarity algorithms, other similarity-basedalgorithms, etc. Data model(s) 114 can be created from example inputs.Data model(s) 114 can analyze data to make predictions or decisions. Forinstance, in at least one example, payment processing service 102 cantrain data model(s) 114 to make recommendations with respect to merchantgroup membership and which merchant of the merchant group may be bestsuited, or recommended, to communicate a response to an inquiry fromanother merchant within the merchant group, based at least in part onmerchant information 110. In such an example, data model(s) 114 can betrained to output a similarity score representative of a similaritybetween two or more merchants using supervised learning algorithms(e.g., artificial neural networks, Bayesian statistics, support vectormachines, decision trees, classifiers, k-nearest neighbor, etc.),unsupervised learning algorithms (e.g., artificial neural networks,association rule learning, hierarchical clustering, cluster analysis,etc.), semi-supervised learning algorithms, deep learning algorithms,etc. Additional details associated with training data model(s) 114 aredescribed below with reference to FIGS. 2-4 . The similarity score canbe used to inform group memberships.

In at least one example, payment processing service 102 can analyzemerchant information 110 utilizing metric(s) and/or data model(s) 114 todetermine how to group merchants. In at least one example, paymentprocessing service 102 can analyze merchant information 110 utilizingmetric(s) and/or data model(s) 114 to determine which merchants aresimilar such that they can be grouped in a same merchant group. Forinstance, based at least in part on determining that a firstcharacteristic is shared by merchant A 104A and merchant B 104B (e.g.,both merchants are associated with a same characteristic), paymentprocessing service 102 can associate merchant A 104A and merchant B 104Bwith merchant group 116A formed on the basis of the sharedcharacteristic. In this way, payment processing service 102 can manageand route communications to different merchants 104 within a particularmerchant group 116 using different communication channels and/ordifferent communication types. For example, a communication from amerchant (e.g., merchant A 104A) in a merchant group (e.g., merchantgroup 116A) can be routed to another merchant in merchant group 116A by(1) a direct message 118 to another member of merchant group 116A, (2) apost to a message board or other internet forum associated with merchantgroup 116A, (3) participation in in a group chat with other members ofmerchant group 116A, etc. In one example, payment processing service 102can provision the merchant social network to enable communicationsbetween merchants associated with the merchant group (e.g., merchant A104A and merchant B 104B). In one instance, communication is enabled bymeans of a direct communication channel between the merchants 104A,104B. As used herein, a “direct communication channel” refers acommunication sent by a merchant (e.g., via a device operated by themerchant) to another merchant (e.g., to a device operated by the othermerchant) via the payment processing service.

Moreover, payment processing service 102 can select a particularcommunication channel and/or communication type to use for acommunication based on at least one of an analysis of the urgency of theinquiry (e.g., POS device malfunction has previously lead to decreasedsales with other merchants within the merchant group) or the preferredcommunication type (e.g., direct message, post, group chat, etc.)utilized by a merchant during a particular time as determined by paymentprocessing service 102.

Merchant group 116B can include one or more merchants 104 that share oneor more other characteristics, merchant group 116N can include one ormore merchants 104 that share one or more other characteristics, and soon. In some examples, merchants 104 can be grouped based at least inpart on a similarity score output by the data model(s) 114. As describedabove, in some examples, merchant A 104A and/or merchant B 104B can beassociated with more than one merchant group. Additionally, one or moreadditional merchants can also be associated with merchant group 116A.

In at least one example, upon determining that a merchant, for examplemerchant A 104A, is associated with a merchant group, for examplemerchant group 116A, payment processing service 102 notifies merchant A104A that the merchant qualifies for membership in merchant group 116Aand informs merchant A 104A that the merchant can be associated withmerchant group 116A upon election to join merchant group 116A. In suchan example, a notification can be sent from payment processing service102 to merchant A 104A by direct message that is presented on merchantdevice 106A of merchant A 104A. Merchant A 104A can make an election viaUI 108A on merchant device 106A. In an additional and/or alternativeexample, a direct message can be surfaced by payment processing service102 to merchant A 104A through a webpage associated with paymentprocessing service 102, and merchant A 104A can make an election byselecting an option on the webpage. In at least one example, paymentprocessing service 102 can associate merchant A 104A with merchant group116A upon receiving an indication of the election by merchant A 104A.

In another example, payment processing service 102 associates merchant A104A with merchant group 116A without an affirmative election bymerchant A 104A (e.g., automatically). In at least one example, uponassociating merchant A 104A with merchant group 116A, payment processingservice 102 can send a notification to merchant A 104A by direct messagethat can be presented on merchant device 106A of merchant A 104A and/orthat can be surfaced through a webpage associated with paymentprocessing service 102.

When merchants 104 (e.g., merchant A 104A, merchant B 104B) areassociated with (or are “members of”) a merchant group (e.g., merchantgroup 116A), merchants 104 can use one or more social networkingservices to interact and/or exchange information. For example, merchants104 can communicate with each other in different ways, using differentcommunication types. For instance, a merchant (e.g., merchant A 104A) ina merchant group (e.g., merchant group 116A) can (1) send a directmessage 118 to another member of the merchant group (e.g., “Where do youbuy your coffee beans?”), (2) post to a message board or other internetforum associated with the merchant group, (3) engage in a group chatwith other members of the merchant group, (4) browse or search themerchant group message board content, etc. The content of the variouscommunications can be recommendations, announcements, questions,advertisements, etc.

For instance, merchants 104 can communicate with each other by usingdirect messaging (e.g., text message, email, chat, etc.), wherein adirect message is a communication that can be transmitted to designatedmembers of merchant group 116A instead of to merchant group 116A as awhole. In at least one example, merchants 104 within merchant group 116Acan directly message one another. As an example, merchant B 104B can usemerchant device 106B to send direct message 118 to merchant device 106Aof merchant A 104A based at least in part on their joint membership inmerchant group 116A. In an example, direct message 118 can be receivedby payment processing service 102 (e.g., from merchant device 106B), andpayment processing service 102 can cause direct message 118 to bepresented on merchant device 106A of the recipient(s). In an additionaland/or alternative example, direct message 118 can be surfaced tomerchant A 104A through a website associated with payment processingservice 102. In another example, merchants 104 can send and/or receivedirect messages to/from the payment processing service 102.

In at least one example, merchants 104 in a merchant group (e.g.,merchant group 116A) can post to a message board, or other internetforum, wherein a post can be accessed and/or viewed by any/all membersof the merchant group. The posts can be questions, general announcements(e.g., announcements about events), recommendations, advertisements,etc. For instance, merchant A 104A can post to a message board ofmerchant group 116A about a technical issue that merchant A 104A isexperiencing in order to seek the assistance of other merchants inmerchant group 116A that may have experienced a similar issue, and thatmay have suggestions for resolution.

Additionally, merchants 104 can use a group chat capability provided bypayment processing service 102 as part of the merchant social network. Agroup chat provides for real-time communications to be transmitted toone or more members of a merchant group (e.g., merchant group 116A) andenables display of communications either on a merchant device (e.g.,merchant device 106A, 106B) or on a webpage associated with paymentprocessing service 102.

Additionally, merchants 104 can browse or search one or more messageboards associated with a merchant group (e.g., merchant group 116A) towhich they belong to look for posts about a topic. Merchants 104 aregiven access to the message board by payment processing service 102 byvirtue of membership in merchant group 116A. For example, a merchantthat recently opened a business can browse information in and related tothe merchant group to learn about one or more aspects of the business,refined by particular characteristic(s) the members of merchant group A116A share. Payment processing service 102 can additionally oralternatively sort the posts on a message board of merchant group 116such that certain posts appear at the top of the page.

Payment processing service 102 can set parameters and settings for thecommunications each merchant group 116 can use. For example, paymentprocessing service 102 can set a parameter for merchant group 116A thatenables all merchants in merchant group 116A to use a message boardfunction but does not allow the merchants to use a direct messagefunction. In another example, payment processing service 102 can set aparameter for an individual merchant A 104A in merchant group 116A thatallows individual merchant A 104A to view a message board but prohibitsmerchant A 104A from posting to the message board.

Merchants 104 in merchant group 116 can receive notifications related tothe communications of members of merchant group 116. For example,payment processing service 102 can send a merchant, such as merchant A104A, a notification that is presented via a display of a correspondingmerchant device, such as merchant device 106A. The notification can bein the form of a text message, an email, a push notification, a sound, anotification associated with a dashboard, a notification associated withthe message board, etc. For example, payment processing service 102 cantransmit to a merchant device 106A a time-sensitive notificationaffecting merchants 104 in merchant group 116A, such as a technicalproblem with a certain model of POS device used by at least somemerchants 104 in merchant group 116A. In an example, a notification canbe presented using UI 108A via a web browser or an application, such asa mobile application or desktop application, which can be provided bypayment processing service 102, or which can be an otherwise dedicatedapplication.

Payment processing service 102 can offer incentives to merchants 104 forparticipating in merchant group 116. For example, payment processingservice 102 can send a direct message to merchant A 104A that offers areward to merchant A 104A for posting answer(s) to question(s) thatother merchant(s) have posted in merchant group 116A. For instance, anincentive can include free (or discounted) processing for merchant A104A from payment processing service 102 or free (or discounted)advertising space on a page associated with payment processing service102.

As illustrated in FIG. 1 , techniques described herein are directed tomerchant social networks that use merchant groups to connect merchantswith like characteristics. As described above, techniques illustrated inFIG. 1 can increase the quality and efficiency of communications betweenmerchants—and between merchants and the payment processing service—bymeans of merchant groups. Accordingly, linking similar merchants 104 canprovide improvements such as reducing merchant contact with the supportteam of payment processing service 102 and increasingmerchant-to-merchant communications. As described above, merchants canhave a higher degree of trust in the relevance and/or credibility ofinformation received from or in a merchant group, at least because themerchants know that the source of the information is merchants that thepayment processing service has determined are similar to them.

FIG. 2 illustrates an example environment 200 for a social network formerchants, according to some implementations. Environment 200 caninclude one or more merchant computing devices 202, which cancommunicate with one or more service computing device(s) 204 via one ormore networks 206. In at least one example, merchant computing device(s)202 and/or service computing device(s) 204 can also communicate withthird-party source(s) and/or system(s) 208 via network(s) 206.

A merchant (not shown in FIG. 2 ) can operate merchant computingdevice(s) 202. In at least one example, merchant computing device(s) 202can be any suitable type of computing device, e.g., portable,semi-portable, semi-stationary, or stationary. Some examples of merchantcomputing device(s) 202 can include tablet computing devices; smartphones and mobile communication devices; laptops, netbooks and otherportable computers or semi-portable computers; desktop computingdevices, terminal computing devices and other semi-stationary orstationary computing devices; dedicated register devices; wearablecomputing devices, or other body-mounted computing devices; augmentedreality devices; or other computing devices capable of sendingcommunications and performing the functions according to the techniquesdescribed herein. Merchant devices 104 as described above with referenceto FIG. 1 can correspond to merchant computing device(s) 202.

In the illustrated example, merchant computing device(s) 202 can includeone or more processors 210, one or more computer-readable media 212, oneor more communication interfaces 214, and one or more input/output (I/O)devices 242. Each processor 210 can itself include one or moreprocessors or processing cores. For example, processor(s) 210 can beimplemented as one or more microprocessors, microcomputers,microcontrollers, digital signal processors, central processing units,state machines, logic circuitries, and/or any devices that manipulatesignals based on operational instructions. In some examples,processor(s) 210 can be one or more hardware processors and/or logiccircuits of any suitable type specifically programmed or configured toexecute the algorithms and processes described herein. Processor(s) 210can be configured to fetch and execute computer-readableprocessor-executable instructions stored in computer-readable media 212.

Depending on the configuration of merchant computing device(s) 202,computer-readable media 212 can be an example of tangible non-transitorycomputer storage media and can include volatile and nonvolatile memoryand/or removable and non-removable media implemented in any type oftechnology for storage of information such as computer-readableprocessor-executable instructions, data structures, program modules orother data. Computer-readable media 212 can include, but is not limitedto, RAM, ROM, EEPROM, flash memory, solid-state storage, magnetic diskstorage, optical storage, and/or other computer-readable mediatechnology. Further, in some examples, merchant computing device(s) 202can access external storage, such as RAID storage systems, storagearrays, network attached storage, storage area networks, cloud storage,or any other medium that can be used to store information and that canbe accessed by processor(s) 210 directly or through another computingdevice or network. Accordingly, computer-readable media 212 can becomputer storage media able to store instructions, modules, orcomponents that can be executed by processor(s) 210. Further, whenmentioned, non-transitory computer-readable media exclude media such asenergy, carrier signals, electromagnetic waves, and signals per se.

Computer-readable media 212 can be used to store and maintain any numberof functional components that are executable by processor(s) 210. Insome implementations, these functional components comprise instructionsor programs that are executable by processor(s) 210 and that, whenexecuted, implement operational logic for performing the actions andservices attributed above to merchant computing device(s) 202.Functional components stored in computer-readable media 212 can includea user interface (UI) for social network access (UI 217) to allow themerchant to access the merchant group(s) and merchant application 218,which can include transaction module 220 and dashboard module 222.

Merchant computing device(s) 202 can include an instance of UI 217 toallow the merchant to access and use the merchant group(s). UI 217 cancorrespond to UI 108A and/or UI 108B described above with reference toFIG. 1 . In at least one example, UI 217 can be presented via a webbrowser, or the like, that enables access to the merchant socialnetwork. In other examples, UI 217 can be presented via an application,such as a mobile application or desktop application, which can beprovided by the payment processing service, or which can be an otherwisededicated application. In at least one example, UI 217 can receiveinstructions associated with a user interface from the paymentprocessing service. UI 217 can utilize the instructions for presentingUI 217 to facilitate (1) joining (or dropping out of) a merchant groupand/or (2) interacting with the merchant social network.

For instance, in at least one example UI 217 can receive a notificationthat the merchant is qualified to join a merchant group. In such anexample, UI 217 can present the notification to the merchant (e.g., viaa display of the merchant computing device(s) 202). The notification caninclude a control that enables the merchant to interact with UI 217 toelect to join the merchant group. For instance, the merchant can actuatethe control such to indicate his/her desire to join the merchant group,and UI 217 can send an indication of the merchant's desire to servicecomputing device(s) 204. Additionally and/or alternatively, UI 217 canreceive a notification that the merchant has been added to a merchantgroup (e.g., automatically). Moreover, in at least one example, UI 217can enable the merchant to remove itself from a merchant group (e.g., byinteracting with a control or other mechanism to indicate its desire tobe removed from a merchant group).

In another example, UI 217 can receive and present a notificationassociated with interactions between merchants of the merchant group.For instance, UI 217 can receive and present a notification to themerchant (e.g., via a display of the merchant computing device(s) 202)that another merchant has posted a message on a message board associatedwith a merchant group.

In an additional and/or alternative example, UI 217 can includecontrol(s) to enable a merchant to receive or transmit direct messagesto/from members of a merchant group or to/from the payment processingservice (e.g., via email, text message, chat, etc.). For instance, UI217 can present a control in association with an email template toenable a merchant to draft an email to be sent to one or more members ofa particular merchant group. Actuation of such a control can cause theemail to be sent to the one or more members via service computingdevice(s) 204.

In an additional and/or alternative example, UI 217 can includecontrol(s) to allow a merchant to post a message to one or more messageboards. For instance, UI 217 can present a control in association withan input mechanism to enable a merchant to post a post to a messageboard associated with a merchant group via service computing device(s)204.

In an additional and/or alternative example, UI 217 can includecontrol(s) to allow a merchant to browse and/or search posts on one ormore message boards. For instance, UI 217 can present a controlassociated with a search functionality to enable a merchant to searchinformation posted on a message board related to one or more aspects ofthe business of the merchant.

In an additional and/or alternative example, UI 217 can includecontrol(s) to allow a merchant to engage in a group chat with othermembers of the merchant group by sending messages (e.g., UI 217 canpresent a control in association with a message template to enable amerchant to draft a message to be included in the group chat forum viathe service computing device(s) 204). UI 217 can also include control(s)to allow a merchant to view and/or search messages of the othermerchants in the group chat (e.g., via a display of the merchantcomputing device(s) 202) from the group chat.

In at least one example, merchant computing device(s) 202 can include aninstance of merchant application 218 that can be executed on merchantcomputing device(s) 202. Merchant application 218 can providepoint-of-sale (POS) functionality to merchant computing device(s) 202 toenable the merchant to accept payments from one or more customers at aPOS location. For example, the merchant can use merchant computingdevice(s) 202 to accept payments through various different types ofpayment instruments, e.g., payment cards, electronic payment, cash orcheck, at the POS location from the one or more customers. In at leastone example, transaction module 220 can present various user interfacesto enable a merchant to conduct transactions, receive payments, and soforth. Further, the dashboard module 222 can enable the merchant tomanage transactions, payments, and so forth, via a dashboard. For thepurpose of this discussion, a dashboard can be a user interface thatprovides an at-a-glance view of key information (e.g., associated withtransactions, payments, etc.). In at least one example, UI 217 can bepresented in association with a dashboard presented via the dashboardmodule 222.

Furthermore, computer-readable media 212 can include additionalfunctional components, such as operating system 224 for controlling andmanaging various functions of merchant computing device(s) 202 and forenabling basic user interactions. In addition, computer-readable media212 can also store data, data structures and the like, that are used bythe functional components. Depending on the type of merchant computingdevice(s) 202, computer-readable media 212 can also optionally includeother functional components and data, such as other modules and data226, which can include programs, drivers, etc., and the data used orgenerated by the functional components. For instance, in some examples,merchant computing device(s) 202 can include a payroll module, aninventory management module, an employee management module, a financingmodule, an appointment module, etc., which can facilitate payrollservices, inventory management services, employee management services,financing services, appointment services, etc., respectively. Further,merchant computing device(s) 202 can include many other logical,programmatic and physical components, of which those described aremerely examples that are related to the discussion herein.

Communication interface(s) 214 can include one or more interfaces andhardware components for enabling communication with various otherdevices, such as over network(s) 206 or directly. For example,communication interface(s) 214 can enable communication through one ormore of the Internet, cable networks, cellular networks, wirelessnetworks (e.g., Wi-Fi) and wired networks, as well as close-rangecommunications such as Bluetooth®, Bluetooth® low energy, and the like,as additionally enumerated elsewhere herein.

Merchant computing device(s) 202 can further include one or more I/Odevices 216. I/O devices 216 can include speakers, a microphone, acamera, and various user controls (e.g., buttons, a joystick, akeyboard, a keypad, etc.), a haptic output device, and so forth.

In at least one example, merchant computing device(s) 202 can includedisplay 228. Depending on the type of computing device(s) used asmerchant computing device(s) 202, display 228 can employ any suitabledisplay technology. For example, display 228 can be a liquid crystaldisplay, a plasma display, a light emitting diode display, an OLED(organic light-emitting diode) display, an electronic paper display, orany other suitable type of display able to present digital contentthereon. In some examples, display 228 can have a touch sensorassociated with display 228 to provide a touchscreen display configuredto receive touch inputs for enabling interaction with a graphicinterface presented on display 228. Accordingly, implementations hereinare not limited to any particular display technology. Alternatively, insome examples, merchant computing device(s) 202 may not include display228, and information can be presented by other means, such as aurally.

In addition, merchant computing device(s) 202 can include or can beconnectable to card reader 230. In some examples, card reader 230 canplug in to a port in merchant computing device(s) 202, such as amicrophone/headphone port, a data port, or other suitable port. Cardreader 230 can include a read head for reading a magnetic strip of apayment card, and further can include encryption technology forencrypting the information read from the magnetic strip. Alternatively,numerous other types of card readers can be employed with merchantcomputing device(s) 202 herein, depending on the type and configurationof merchant computing device(s) 202.

Other components included in merchant computing device(s) 202 caninclude GPS device 232 that is able to indicate location information.Further, merchant computing device(s) 202 can include one or moresensors 234, such as an accelerometer, gyroscope, compass, proximitysensor, camera, microphone, and/or a switch, as discussed above.Additionally, merchant computing device(s) 202 can include various othercomponents that are not shown, examples of which include removablestorage, a power source, such as a battery and power control unit, abarcode scanner, a printer, a cash drawer, and so forth.

As described above, techniques described herein are directed to usingmerchant groups to enable social networking of merchants that areassociated with a payment processing service. In at least one example,the payment processing service can operate service computing device(s)204. Service computing device(s) 204 can include one or more servers orother types of computing devices that can be embodied in any number ofways. For example, in the example of a server, the modules, otherfunctional components, and data can be implemented on a single server, acluster of servers, a server farm or data center, a cloud-hostedcomputing service, a cloud-hosted storage service, and so forth,although other computer architectures can additionally or alternativelybe used.

Further, while the figures illustrate the components and data of servicecomputing device(s) 204 as being present in a single location, thesecomponents and data can alternatively be distributed across differentcomputing devices and different locations in any manner. Consequently,the functions can be implemented by one or more service computingdevices, with the various functionality described above distributed invarious ways across the different computing devices. Multiple servicecomputing device(s) 204 can be located together or separately, andorganized, for example, as virtual servers, server banks, and/or serverfarms. The described functionality can be provided by the servers of asingle entity or enterprise, or can be provided by the servers and/orservices of multiple different customers or enterprises.

In the illustrated example, service computing device(s) 204 can includeone or more processors 236, one or more computer-readable media 238, oneor more communication interfaces 240, and one or more input/outputdevices 242. Each of the one or more processors 236 can be a singleprocessing unit or a number of processing units, and can include singleor multiple computing units or multiple processing cores. The one ormore processors 236 can be implemented as one or more microprocessors,microcomputers, microcontrollers, digital signal processors, centralprocessing units, state machines, logic circuitries, and/or any devicesthat manipulate signals based on operational instructions. For example,one or more processors 236 can be one or more hardware processors and/orlogic circuits of any suitable type specifically programmed orconfigured to execute the algorithms and processes described herein. Oneor more processors 236 can be configured to fetch and executecomputer-readable instructions stored in computer-readable media 238,which can program one or more processors 236 to perform the functionsdescribed herein.

Computer-readable media 238 can include volatile and nonvolatile memoryand/or removable and non-removable media implemented in any type oftechnology for storage of information, such as computer-readableinstructions, data structures, program modules, or other data. Suchcomputer-readable media 238 can include, but is not limited to, RAM,ROM, EEPROM, flash memory or other memory technology, optical storage,solid state storage, magnetic tape, magnetic disk storage, RAID storagesystems, storage arrays, network attached storage, storage areanetworks, cloud storage, or any other medium that can be used to storethe desired information and that can be accessed by a computing device.Depending on the configuration of service computing device(s) 204,computer-readable media 238 can be a type of computer-readable storagemedia and/or can be a tangible non-transitory media to the extent thatwhen mentioned, non-transitory computer-readable media exclude mediasuch as energy, carrier signals, electromagnetic waves, and signals perse. Computer-readable media 238 can be used to store any number offunctional components that are executable by one or more processors 236.In many implementations, these functional components compriseinstructions or programs that are executable by one or more processors236 and that, when executed, specifically configure one or moreprocessors 236 to perform the actions attributed above to paymentprocessing service 102. Functional components stored incomputer-readable media 238 can include merchant networking module 244,which can include grouping module 246 and interaction module 248, andtraining module 250, which can store one or more data model(s) 252.

Service computing device(s) 204 can include an instance of merchantnetworking module 244. Merchant networking module 244 can be configuredto facilitate forming and/or updating of merchant groups and/or tofacilitate interactions between merchants of the merchant groups. In atleast one example, merchant networking module 244 can include aninstance of grouping module 246 and an instance of interaction module248.

In at least one example, grouping module 246 can be configured toanalyze merchant information 254 to intelligently determine grouping(s)of merchants. Merchant information 254 can be stored in a database incomputer-readable media 238, as described below. As described above,merchant information 254 can include information associated with amerchant. Merchant information 254 can include one or more merchantcharacteristics. For instance, merchant information 254 can correspondto merchant characteristics that can include, but are not limited tocharacteristics specific to a merchant itself, for example, a type ofmerchant, a merchant category code (“MCC”), a location(s) of a merchant,hours of operation of a merchant, non-profit or for-profit status of amerchant, mobility of a merchant store (e.g., whether the merchantoperates from a food truck or a building), inventory of a merchant,square footage of a brick-and-mortar store of a merchant, items offeredfor sale by a merchant, etc. Such merchant information 254 can bereceived by the service computing device(s) 204 from a device operatedby a merchant (e.g., merchant computing device(s) 202), for instancewhen the merchant sets up an account with the payment processing serviceor at a subsequent time. Additionally and/or alternatively, merchantinformation 254 associated with such merchant characteristics can bedetermined based on information received from one or more third-partysource(s) and/or system(s) 208. Additionally, merchant information 254can be analyzed to determine merchant characteristic informationassociated with merchants, and from the merchant characteristicinformation, a shared characteristic of the merchants can be determined.

As described above, in some examples, merchant computing device(s) 202can execute an instance of merchant application 218 that is installed toconfigure the merchant computing device(s) 202 as a POS terminal. Insuch examples, merchant application 218 (e.g., via the transactionmodule 220) can communicate transaction data to service computingdevice(s) 204. In at least one example, merchant information 254 caninclude transaction data received from merchant application 218. In atleast one example, merchant information 254 can include characteristicsassociated with the transaction data. For instance, characteristics ofmerchants can also include, but are not limited to, characteristicsassociated with merchant transactions, which can include, for example, avolume of transactions processed by a merchant (or on behalf of themerchant), a frequency of transactions processed by a merchant (or onbehalf of the merchant), an average transaction amount for transactionsprocessed by a merchant (or on behalf of the merchant), a transactionamount for transactions occurring during a period of time that areprocessed by a merchant (or on behalf of the merchant), an averagetransaction amount for transactions occurring during a period of timethat are processed by a merchant (or on behalf of the merchant), mostpopular time(s) of day for transactions processed by a merchant (or onbehalf of the merchant), a payment history associated with a merchant,etc.

Moreover, characteristics of merchants can also include, but are notlimited to, characteristics associated with various entities associatedwith a merchant, which can include, for example, suppliers used by amerchant, customers of a merchant, merchants related to a merchant(e.g., through common ownership), a number or identity of employees of amerchant, etc. Merchant information 254 associated with suchcharacteristics can be determined based on various merchant interactionswith the payment processing system (e.g., inventory services, employeemanagement services, etc.). In at least one example, characteristics ofmerchants can also include, but are not limited to, characteristicsassociated with a relationship between a merchant and payment processingservice, which can include, for example, a type of POS device used by amerchant, payment processing service services used by a merchant (e.g.,invoice services, appointment services, POS services, e-commerceservices), support requests, etc. Merchant information 254 associatedwith such characteristics can be determined based on additional and/oralternative merchant interactions with the payment processing system.Additional and/or alternative merchant information 254 can be imagined.

In at least one example, grouping module 246 can be configured tointelligently determine, by utilization of one or more data models 252trained by training module 250, a similarity score reflecting asimilarity between a merchant and another merchant, or between amerchant and a group of merchants. For instance, grouping module 246 canutilize data model(s) 252 to calculate a similarity score indicative ofsimilarity between the merchant and the other merchant (or the merchantgroup) based on one or more merchant characteristics (e.g., MCC,location, inventory, etc.). That is, a similarity score is associatedwith a degree of similarity between a merchant and at least one othermerchant (or merchant group).

In at least one example, the similarity score can be indicative of anextent to which merchants share characteristics. For instance, asimilarity score that meets or exceeds a threshold can indicate that twoor more merchants share at least one characteristic. In such an example,a higher similarity score (e.g., close to one on a scale from zero toone) can indicate that the two or more merchants share multiplecharacteristics. Alternatively, a lower similarity score (e.g., close tozero on a scale from zero to one) can indicate that the two or moremerchants do not share any characteristics. Of course, other scales canbe used; a scale from zero to one is provided for an example. In someexamples, particular characteristics can be weighted such to havedifferent effects on a similarity score. For instance, in a non-limitingexample, if merchant category code is valued more than geolocation,merchant category code can be weighted such that it increases thesimilarity score more so than geolocation. Additionally, oralternatively, in another non-limiting example, geolocation can beirrelevant and may not factor into the similarity analysis. In such anexample, geolocation can be associated with a weight such that it doesnot impact the similarity score.

As described above, based at least in part on analyzing merchantinformation 254, data model(s) 252 can output a similarity scorerepresentative of a similarity between a merchant and at least one othermerchant. Merchants with a similarity score that meets or exceeds athreshold can be associated with a same merchant group. Additionally, oralternatively, when a merchant and a merchant group have a similarityscore that meets or exceeds a threshold, the merchant can be associatedwith the merchant group. For instance, grouping module 246 can accessmerchant information 254 associated with two or more merchants and canleverage data model(s) 252 to analyze merchant information 254.Accordingly, grouping module 246 can compare the similarity score with athreshold and, based at least in part on determining that the similarityscore meets or exceeds a threshold, grouping module 246 can associatethe merchant and the at least one other merchant with a same merchantgroup. If the at least one other merchant is already part of a merchantgroup, grouping module 246 can associate the merchant with the merchantgroup.

In some examples, grouping module 246 can determine similarityresponsive to an occurrence of one or more prompting events. Forexample, grouping module 246 can determine similarity (1) upon receivinga registration from a new merchant, (2) upon receiving a membershiprequest from a merchant (e.g., a request to participate in the merchantsocial network, a request to change merchant groups, etc.), (3) uponreceiving a membership request from the support team, (4) upon receivinginformation indicating that merchant information 254 has changed, and/or(5) at a regular frequency. That is, responsive to an occurrence of aprompting event, grouping module 246 can access merchant information 254associated with two or more merchants, and group merchant(s) based on adetermined similarity between two or more merchants.

In an example, grouping module 246 can determine similarity uponreceiving registration information associated with a merchantregistering for service with the payment processing service. Forexample, merchant information 254 can be included as part ofregistration data that is transmitted by merchant computing device(s)202 via network(s) 206 to service computing device(s) 204 at the time ofmerchant registration. Other modules 258 of service computing device(s)204 receive the registration information and transmit it to groupingmodule 246 at additional and/or alternative times. Responsive toreceiving merchant information 254, grouping module 246 can analyzemerchant information 254 to determine whether to assign the merchant toany merchant group(s) and/or which merchant group(s) to assign themerchant.

In an additional and/or alternative example, grouping module 246 canreceive a membership request from a merchant already receiving servicesfrom the payment processing service. For example, a merchant can send amembership request via a control of UI 217 to be added to anon-specified merchant group, or a particular merchant group. Merchantcomputing device(s) 202 can transmit the membership request vianetwork(s) 206 to service computing device(s) 204. Grouping module 246can receive the membership request and, responsive to receiving themembership request, can determine a similarity between the merchant andthe particular merchant group or to one or more merchant groups,generally.

In response to an occurrence of a prompting event, grouping module 246can determine similarity. In an example, grouping module 246 can accessmerchant information 254, which, as described above, can be stored in adatabase. In at least one example, the database storing merchantinformation 254 can be arranged in merchant profiles associated withindividual merchants. The data in the database can be received frommerchant computing device(s) 202, third-party source(s) and/or system(s)208, etc., as described above. In at least one example, based at leastin part on accessing merchant information 254, grouping module 246 candetermine a similarity between the merchant and another merchant (ormerchant group) based on one or more merchant characteristics (e.g., byusing data model(s) 252). In at least one example, the similarity can berepresented as a similarity score. Based upon the similarity scoremeeting or exceeding a threshold, grouping module 246 can associate amerchant with another merchant (or with a particular merchant group).

In at least one example, based on an association between the merchants,grouping module 246 can add merchant(s) to a particular merchant group.When merchants are associated with (or are “members of”) a merchantgroup, merchants can use one or more social networking services tointeract and/or exchange information. For example, merchants cancommunicate with each other in different ways, using differentcommunication types. For instance, a merchant in a merchant group can(1) send a direct message to another member of the merchant group, (2)post to a message board or other internet forum associated with themerchant group, (3) engage in a group chat with other members of themerchant group, (4) browse or search the merchant group message boardcontent, etc. The content of the various communications can berecommendations, announcements, questions, advertisements, etc. In oneexample, upon association of a merchant with a merchant group,communications between the merchant and the merchant group are enabledby service computing device(s) 204 provisioning the merchant socialnetwork associated with the merchant group to enable communicationbetween merchants of the merchant group. In one instance, communicationis enabled by means of a direct communication channel between themerchants.

In some examples, grouping module 246 can add a merchant to a merchantgroup with which another (similar) merchant is already associated. Inother examples, grouping module 246 can add a merchant and another(similar) merchant to a new merchant group. In at least one example, thegrouping module 246 can add the merchant(s) to the merchant group byadding an indicator of such merchant group to respective merchantprofile(s) of the merchant(s). Additionally and/or alternatively, thegrouping module 246 can add the merchant(s) to the merchant group bymapping, or otherwise associating merchant profile(s) associated withthe merchant(s) to the merchant group.

In an example, adding the merchant to the merchant group can occurwithout receiving an election from the merchant to join. That is, insome examples, grouping module 246 can add a merchant to a merchantgroup automatically. Alternatively, in some examples, a merchant canelect to join a merchant group prior to the merchant being added to themerchant group. In such examples, grouping module 246 can send a deviceoperated by the merchant (e.g., merchant computing device(s) 202) anindication of eligibility to join at least one merchant group, togetherwith an indication of one or more steps the merchant can follow toaffirmatively elect to join merchant group (e.g., via interaction withUI 217). If grouping module 246 receives an indication of an election tojoin the merchant group, grouping module 246 can associate the merchantwith the merchant group. In either example (e.g., where the merchant isadded automatically and/or the merchant is added based on an election),grouping module 246 can send a notification to a device operated by themerchant (e.g., merchant computing device(s) 202) to inform the merchantthat the merchant has been made a member of the merchant group.

Merchant networking module 244 can also include interaction module 248.In at least one example, interaction module 248 can coordinatecommunications among merchant computing devices 202 and/orcommunications between merchant computing devices 202 and servicecomputing device(s) 204, etc.

In at least one example, interaction module 248 can receive acommunication from merchant computing device(s) 202 of a merchant thatis a member of a merchant group. The communication can be a request bythe member to post to a message board or other forum associated with themerchant group, a direct message to other merchant(s), a request toengage in a group chat with other member(s) of the merchant group, anindication of a search query the merchant would like to implement on amessage board or elsewhere on the merchant social network, a request tobrowse the posts of a message board or other forum associated with themerchant group, etc.

In at least one example, a communication can include metadata indicatinga merchant that sent the communication, intended recipient(s) of thecommunication (e.g., merchant group(s), individual merchant(s), etc.), acommunication type, a data stamp, a time stamp, etc. In an example,interaction module 248 can analyze the metadata associated with thecommunication to determine the merchant who sent the communication, theintended recipient(s) (e.g., relevant merchant group(s) and/orindividual merchant(s) within merchant group(s)), the communicationtype, etc., in order to determine where to route the communication.

For instance, interaction module 248 can determine the merchant who sentthe communication based at least in part on metadata associated with thecommunication having an indicator of identity of the merchant (e.g.,merchant identifier, merchant device address, etc.). In at least oneexample, interaction module 248 can determine the intended recipient(s)for the communication. The intended recipient(s) can be one or moremerchant groups and/or individual merchant(s) within the one or moremerchant groups. In at least one example, interaction module 248 candetermine the merchant group(s) to which the communication pertainsbased at least in part on (1) metadata associated with the communicationhaving an indicator of the merchant group(s) from which the merchant issending the communication (e.g., an email template generated when themerchant was active on the message board for a particular merchantgroup), (2) a selection by the merchant of a control of UI 217indicating the relevant merchant group, and/or (3) entry of the merchantgroup(s) by the merchant into a text field of UI 217. In some examples,interaction module 248 can determine the merchant group(s) to which thecommunication pertains responsive to receiving a communication (e.g.,based on mappings or other associations between the merchant who sentthe communication and one or more merchant group(s)). Furthermore,interaction module 248 can determine the intended recipient(s) of thecommunication based at least in part on the communication type (e.g.,email, text, etc.) and/or fields of the communication (e.g., “to,”addressee, etc.). In at least one example, interaction module 248 candetermine the communication type (e.g., email, text, message board post,etc.) based at least in part on data or metadata associated with thecommunication having an indicator or communication type. In someexamples, interaction module 248 can determine the intended recipient(s)based at least partly on the communication type.

Based at least in part on determining the intended recipient(s) and/orcommunication type, interaction module 248 can transmit thecommunication to devices operated by the appropriate recipient(s). Thatis, interaction module 248 can route the communication to the relevantmerchant group and/or intended recipient. In at least one example,interaction module 248 can transmit a message to the merchant who sentthe communication indicating the disposition of the communication (e.g.,delivered, posted, forwarded, etc.). Additionally and/or alternatively,interaction module 248 can notify intended recipient(s) (e.g., othermerchant, entire merchant group, etc.) of the communication.

For instance, the communication can be a post to a message board of aparticular merchant group. Interaction module 248 can cause the post tobe presented via the message board and can send notification(s) tomembers of the particular merchant group indicating that a new post hasbeen added to the message board. Interaction module 248 can transmit amessage to the merchant who sent the communication indicating that thepost has been posted to the message board. In another example, thecommunication can be an email to another merchant of the merchant group.Interaction module 248 can transmit the email to the merchant computingdevice of the other merchant and/or the email can be surfaced to theother merchant through a website associated with payment processingservice. Interaction module 248 can transmit a message to the merchantwho sent the communication indicating that the email has beentransmitted to the intended recipient(s).

In another example, the communication can be a support request sent by amerchant to the payment processing service (e.g., for technical support,etc.), where a support team is the determined intended recipient(s). Insuch an example, interaction module 248 can route the support request toa support team of service computing device(s) 204 (along with anindication of merchant group(s) of which the merchant is a member) sothat the support team can determine a response to the support request.The response to the support request can be based at least in part onprevious communications from other members of any merchant group(s) withwhich the merchant is associated, or based at least in part oninformation associated with merchant group(s) with which the merchant isassociated. In an example, service computing device(s) 204 can determinea response to the support request by performing natural languageprocessing of past communications between the support team and merchantsin the merchant group (or communications between merchants of themerchant group). In an example, service computing device(s) 204 can alsodetermine a response to the support request by text-searching electronicnotes of support agents associated with the support team. Interactionmodule 248 can transmit a message to the merchant who sent the supportrequest that the support request has been transmitted to the supportteam.

In at least one example, interaction module 248 can receive anindication of a search query that a merchant would like to implement ona message board or elsewhere on the merchant social network. Interactionmodule 248 can execute the query on the message board content, forinstance, or on other social network content for which the merchant isauthorized to access by service computing device(s) 204. Interactionmodule 248 can transmit search results to the merchant who made thesearch query.

In another example, interaction module 248 can receive instructions fromanother module 258 of service computing device(s) 204 to present amessage, regarding a topic relevant to a merchant group, as a post on anelectronic message board of the merchant group. Interaction module 248can cause the post to be presented via the message board and can sendnotification(s) to members of the particular merchant group indicatingthat a new post has been added to the message board.

In another example, interaction module 248 can receive an indicationthat a member has asked a question of a merchant group. Interactionmodule 248 can access merchant information 254 associated with theinquiring merchant and the plurality of other merchants associated withthe merchant group. Interaction module 248 can leverage data model(s)252 to analyze merchant information 254 of the inquiring merchant andthe plurality of other merchants. Data model(s) 252 can outputsimilarity scores representative of a similarity between the inquiringmerchant and each of the plurality of other merchants. Interactionmodule 248 can compare the similarity scores and identify (e.g., byranking the similarity scores and identifying the top-ranked merchant) arecommended merchant recipient to answer the question. In one example,interaction module 246 can provision the merchant social networkassociated with the merchant group to enable communication between theinquiring merchant and the recommended merchant recipient. In oneinstance, interaction module 246 can provision the merchant socialnetwork to enable communication by enabling a direct communicationchannel between the inquiring merchant and the recommended merchantrecipient and/or by facilitating access by the direct communicationchannel to a merchant device of the recommended merchant recipient.

Additionally, or alternatively, upon interaction module 248 receiving anindication that a member is asking a question of the member group,interaction module 248 can determine a recommended merchant recipient toanswer the question by analyzing previous communications from, to,between, and/or among the plurality of merchants associated with themerchant group. Based on the question and the previous communications,interaction module 248 can identify at least one recommended merchantrecipient of the plurality of merchants. In one instance, interactionmodule 248 can then provide access to a merchant device of the inquiringmerchant, via a direct communication channel, to a merchant deviceassociated with the recommended merchant recipient.

In another example, interaction module 248 may determine that themerchant asking a question is not a member of a merchant group.Interaction module 248 can associate the merchant with a merchant group,and then proceed to determine a recommended merchant recipient asdescribed above.

Interaction module 248 can receive and transmit other interactions, inaddition to the interactions and communications described above.

In at least one example, service computing device(s) 204 can include aninstance of training module 250. Service computing device(s) 204 cantrain and store data model(s) 252. Training module 250 can train datamodel(s) 252 based on a plurality of training data items such that,given a new input of merchant information 254 associated with amerchant, data model(s) 252 can determine similarities between merchantsand/or between a merchant and a merchant group based on that input. Inat least one example, training module 250 can receive updated trainingdata and can iteratively update data model(s) 252 based at least in parton the updated training data.

In at least one example, training module 250 can utilize machinelearning algorithms to build, modify, or otherwise utilize data model(s)252. In at least one example, the machine learning algorithms caninclude memory-based collaborative filtering algorithms, model-basedcollaborative filtering algorithms, feature-based similarity algorithms,other similarity-based algorithms, etc. In at least one example,training module 250 can access training data for training data model(s)252. The training data can include merchant information 254, which caninclude or correspond to data, and/or merchant characteristicinformation, indicative of characteristics of a plurality of merchants.The training data can also include data associated with groupings ofmerchants and/or similarity scores associated with individual merchantsin a merchant group. In some examples, the groups can be manually formedand labeled. In other examples, the groups can be formed via techniquesdescribed herein. Similarly, in at least one example, similarity scorescan be manually determined and assigned, or similarity scores can bedetermined via techniques described herein.

In at least one example, training module 250 can train data model(s) 252based at least in part on the training data. In such an example,training module 250 can train data model(s) 252 to output a similarityscore representative of a similarity between two or more merchants,which can be used for informing merchant group membership. In at leastone example, training module 250 can train data model(s) 252 usingsupervised learning algorithms (e.g., artificial neural networks,Bayesian statistics, support vector machines, decision trees,classifiers, k-nearest neighbor, etc.), unsupervised learning algorithms(e.g., artificial neural networks, association rule learning,hierarchical clustering, cluster analysis, etc.), semi-supervisedlearning algorithms, deep learning algorithms, etc. Additional detailsassociated with training data model(s) 252 are described below withreference to FIG. 3 .

Additional functional components stored in computer-readable media 238can include operating system 256 for controlling and managing variousfunctions of service computing device(s) 204. In at least one example,computer-readable media 238 can additionally include or maintain otherfunctional components and data, such as other modules and data 258,which can include programs, drivers, etc., and the data used orgenerated by the functional components. Further, service computingdevice(s) 204 can include many other logical, programmatic and physicalcomponents, of which those described above are merely examples that arerelated to the discussion herein.

Communication interface(s) 240 can include one or more interfaces andhardware components for enabling communication with various otherdevices, such as over network(s) 206. For example, communicationinterface(s) 240 can enable communication through one or more of theInternet, cable networks, cellular networks, wireless networks (e.g.,Wi-Fi) and wired networks, as well as close-range communications such asBluetooth®, Bluetooth® low energy, and the like, as additionallyenumerated elsewhere herein.

Service computing device(s) 204 can further be equipped with variousinput/output (I/O) devices 242. Such I/O devices 242 can include adisplay, various user interface controls (e.g., buttons, joystick,keyboard, mouse, touch screen, etc.), audio speakers, connection portsand so forth.

FIGS. 3-5 are flow diagrams illustrating example processes according tosome implementations. The processes of FIGS. 3-5 are illustrated ascollections of blocks in logical flow diagrams, which represent asequence of operations, some or all of which can be implemented inhardware, software or a combination thereof. In the context of software,the blocks can represent computer-executable instructions stored on oneor more computer-readable media that, when executed by one or moreprocessors, program the processors to perform the recited operations.Generally, computer-executable instructions include routines, programs,objects, components, data structures and the like that performparticular functions or implement particular data types. The order inwhich the blocks are described should not be construed as a limitation.Any number of the described blocks can be combined in any order and/orin parallel to implement the process, or alternative processes, and notall of the blocks need be executed. Further, in some examples, some orall of the operations illustrated in one or more of FIGS. 3-5 can becombined with some or all of the operations illustrated in others ofFIGS. 3-5 . For discussion purposes, the processes are described withreference to the environments, architectures and devices described inthe examples herein, although the processes can be implemented in a widevariety of other environments, architectures and devices.

Various instructions, methods, and techniques described herein can beconsidered in the general context of computer-executable instructions,such as program modules stored on computer-readable media, and executedby the processor(s) herein. Generally, program modules include routines,programs, objects, components, data structures, etc., for performingparticular tasks or implementing particular abstract data types. Theseprogram modules, and the like, can be executed as native code or can bedownloaded and executed, such as in a virtual machine or otherjust-in-time compilation execution environment. Typically, thefunctionality of the program modules can be combined or distributed asdesired in various implementations. An implementation of these modulesand techniques can be stored on computer storage media or transmittedacross some form of communication media.

FIG. 3 is a flow diagram illustrating example process 300 for training adata model for determining similarity between merchants. FIG. 3 isdescribed in the context of the environment and/or device(s) describedabove with reference to FIG. 2 , but is not limited to such environmentand/or device(s).

Block 302 illustrates accessing training data that includes merchantinformation associated with a plurality of merchants and indications ofmerchant groups. Training module 250 can access training data fortraining data model(s) 252. The training data can include merchantinformation 254, which can include or correspond to data indicative ofcharacteristics of a plurality of merchants, which are described above.The training data can also include data associated with groupings ofmerchants and/or similarity scores associated with individual merchantsin a merchant group. In some examples, the groups can be manually formedand labeled. In other examples, the groups can be formed via techniquesdescribed herein. Similarly, in at least one example, similarity scorescan be manually determined and assigned, or similarity scores can bedetermined via techniques described herein.

Block 304 illustrates training a data model on the training data via amachine learning mechanism. Training module 250 can train data model(s)252 based at least in part on the training data. In such an example,training module 250 can train data model(s) 252 to output a similarityscore representative of a similarity between two or more merchants,which can be used for informing merchant group membership. In at leastone example, training module 250 can train data model(s) 252 usingsupervised learning algorithms (e.g., artificial neural networks,Bayesian statistics, support vector machines, decision trees,classifiers, k-nearest neighbor, etc.), unsupervised learning algorithms(e.g., artificial neural networks, association rule learning,hierarchical clustering, cluster analysis, etc.), semi-supervisedlearning algorithms, deep learning algorithms, etc.

Block 306 illustrates determining similarities between merchants and/orbetween a merchant and a merchant group based on the data model. In atleast one example, grouping module 246 can be configured tointelligently determine, by utilization of one or more data models 252trained by training module 250, a similarity score reflecting asimilarity between a merchant and another merchant, or between amerchant and a group of merchants. For instance, grouping module 246 canutilize data model(s) 252 to calculate a similarity score indicative ofsimilarity between the merchant and the other merchant (or the merchantgroup) based on one or more merchant characteristics (e.g., MCC,location, inventory, etc.). That is, a similarity score is associatedwith a degree of similarity between a merchant and at least one othermerchant (or merchant group).

In at least one example, the similarity score can be indicative of anextent to which merchants share characteristic(s). For instance, asimilarity score that meets or exceeds a threshold can indicate that twoor more merchants share at least one characteristic. In such an example,a higher similarity score (e.g., close to one on a scale from zero toone) can indicate that the two or more merchants share multiplecharacteristics. Alternatively, a lower similarity score (e.g., close tozero on a scale from zero to one) can indicate that the two or moremerchants do not share any characteristics. Of course, other scales canbe used; a scale from zero to one is provided for an example. In someexamples, particular characteristics can be weighted such to havedifferent effects on a similarity score. For instance, in a non-limitingexample, if merchant category code is valued more than geolocation,merchant category code can be weighted such that it increases thesimilarity score more so than geolocation. Additionally, oralternatively, in another non-limiting example, geolocation can beirrelevant and may not factor into the similarity analysis. In such anexample, geolocation can be associated with a weight such that it doesnot impact the similarity score.

Block 308 illustrates determining merchant group(s) based at least inpart on the similarities. As described above, based at least in part onanalyzing merchant information 254, data model(s) 252 can output asimilarity score representative of a similarity between a merchant andat least one other merchant. Merchants with a similarity score thatmeets or exceeds a threshold can be associated with a same merchantgroup. Additionally, or alternatively, when a merchant and a merchantgroup have a similarity score that meets or exceeds a threshold, themerchant can be associated with the merchant group. For instance,grouping module 246 can access merchant information 254 associated withtwo or more merchants and can leverage data model(s) 252 to analyzemerchant information 254. Accordingly, grouping module 246 can comparethe similarity score with a threshold and, based at least in part ondetermining that the similarity score meets or exceeds a threshold,grouping module 246 can associate the merchant and the at least oneother merchant with a same merchant group. If the at least one othermerchant is already part of a merchant group, grouping module 246 canassociate the merchant with the merchant group. Additional detailsassociated with grouping merchants can be described below with referenceto FIG. 4 .

Block 310 illustrates iteratively updating the data model. In at leastone example, training module 250 can receive updated training data andcan iteratively update data model(s) 252 based at least in part on theupdated training data.

FIG. 4 is a flow diagram illustrating an example process 400 forgrouping similar merchants into merchant groups to enable access tomerchant social network services. FIG. 4 is described in the context ofthe environment and/or device(s) described above with reference to FIG.2 , but is not limited to such environment and/or device(s).

Block 402 illustrates receiving first merchant information associatedwith a first merchant. In at least one example, service computingdevice(s) 204 can receive merchant information 254 associated with afirst merchant. As described above, service computing device(s) 204 canstore merchant information 254 in a database in computer-readable media238, as described below. As described above, merchant information 254can include information associated with a merchant. Merchant information254 can include one or more merchant characteristics. For instance,merchant information 254 can correspond to merchant characteristics thatcan include, but are not limited to characteristics specific to amerchant itself, characteristics associated with merchant transactions,characteristics associated with various entities associated with amerchant, characteristics associated with a relationship between amerchant and payment processing service, etc. Merchant information 254can also be analyzed using data model 252 to define merchantcharacteristic information associated with merchants. In some examples,merchant characteristic information can be the basis of determining ashared characteristic between merchants. As described above, merchantinformation 254 can be received from merchant computing device(s) 202and/or third-party source(s) and/or system(s) 208.

Block 404 illustrates receiving second merchant information associatedwith a second merchant. In at least one example, service computingdevice(s) 204 can receive merchant information 254 associated with asecond merchant. As described above, service computing device(s) 204 canstore merchant information 254 in a database in computer-readable media238, as described below. As described above, merchant information 254can include information associated with a merchant. Merchant information254 can include one or more merchant characteristics. For instance,merchant information 254 can correspond to merchant characteristics thatcan include, but are not limited to characteristics specific to amerchant itself, characteristics associated with merchant transactions,characteristics associated with various entities associated with amerchant, characteristics associated with a relationship between amerchant and payment processing service, etc. As described above,merchant information 254 can be received from merchant computingdevice(s) 202 and/or third-party source(s) and/or system(s) 208.

Block 406 illustrates determining, based at least in part on a datamodel, a similarity score representative of a similarity between thefirst merchant and the second merchant. In at least one example,grouping module 246 can be configured to intelligently determine, byutilization of one or more data models 252 trained by training module250, a similarity score reflecting a similarity between the firstmerchant and the second merchant. In some examples, the second merchantcan be representative of a merchant group.

In at least one example, grouping module 246 can access merchantinformation 254 associated with the first merchant and merchantinformation 254 associated with the second merchant, and can analyzemerchant information 254 with data model(s) 252. As described above,data model(s) 252 can be trained to output a similarity score indicativeof similarity between the first merchant and the second merchant (whichcan be representative of a merchant group) based on one or more merchantcharacteristics (e.g., MCC, location, inventory, etc.). That is,grouping module 246 can leverage data model(s) 252 to determine asimilarity score that is associated with a degree of similarity betweena merchant and at least one other merchant (or merchant group).

Block 408 illustrates determining whether a similarity score meets orexceeds a threshold. In at least one example, grouping module 246 cancompare the similarity score with a threshold.

Block 410 illustrates associating the first merchant and the secondmerchant with a merchant group based on determining that the similarityscore meets or exceeds the threshold. Merchants with a similarity scorethat meets or exceeds a threshold can be associated with a same merchantgroup. Additionally, or alternatively, when a merchant and a merchantgroup have a similarity score that meets or exceeds a threshold, themerchant can be associated with the merchant group. Accordingly, in atleast one example, grouping module 246 can compare the similarity scorewith a threshold and, based at least in part on determining that thesimilarity score meets or exceeds a threshold, grouping module 246 canassociate the first merchant and the second merchant with a samemerchant group. In some examples, the merchant group can be a newlyformed merchant group (with the first merchant and the second merchant).In other examples, if the first merchant or the second merchant isalready part of a merchant group, grouping module 246 can associate theother merchant with the same merchant group.

In at least one example, the grouping module 246 can add the merchant(s)to the merchant group by adding an indicator of such merchant group torespective merchant profile(s) of the merchant(s). Additionally and/oralternatively, the grouping module 246 can add the merchant(s) to themerchant group by mapping, or otherwise associating, merchant profile(s)associated with the merchant(s) to the merchant group.

In at least one example, adding the merchant to the merchant group canoccur without receiving an election from the merchant to join. Forexample, grouping module 246 can add a merchant to a merchant groupautomatically. Alternatively, in some examples, a merchant can elect tojoin a merchant group prior to the merchant being added to the merchantgroup. In such examples, grouping module 246 can send, to a deviceoperated by the merchant (e.g., merchant computing device(s) 202), anindication of eligibility to join at least one merchant group togetherwith an indication of one or more steps the merchant can follow toaffirmatively elect to join merchant group (e.g., via interaction withUI 217). If grouping module 246 receives an indication of an election tojoin the merchant group, grouping module 246 can associate the merchantwith the merchant group.

Block 412 illustrates enabling the first merchant and second merchant toaccess a service associated with a merchant social network based atleast in part on the association with the merchant group. In at leastone example, based on the association between the merchants, groupingmodule 246 can add merchant(s) to a particular merchant group. Whenmerchants are associated with (or are “members of”) a merchant group,merchants can use one or more social networking services to interactand/or exchange information. For example, merchants can communicate witheach other in different ways, using different communication types. Forinstance, a merchant in a merchant group can (1) send a direct messageto another member of the merchant group, (2) post to a message board orother internet forum associated with the merchant group, (3) engage in agroup chat with other members of the merchant group, (4) browse orsearch the merchant group message board content, etc. The content of thevarious communications can be recommendations, announcements, questions,advertisements, etc. Additional details associated with socialnetworking services that are availed to grouped merchants are describedbelow with respect to FIG. 5 .

Block 414 illustrates refraining from associating the first merchant andthe second merchant with a merchant group based on determining that thesimilarity score does not meet or exceed the threshold. Based at leastin part on determining that the similarity score does not meet or exceedthe threshold, grouping module 246 can refrain from associating thefirst merchant and the second merchant with a same merchant group.

FIG. 5 is a flow diagram illustrating an example process 500 forfacilitating interactions via a merchant social network. FIG. 5 isdescribed in the context of the environment and/or device(s) describedabove with reference to FIG. 2 , but is not limited to such environmentand/or device(s).

Block 502 illustrates receiving a communication from merchant computingdevice(s) associated with a merchant who is a member of at least onemerchant group of a merchant social network. In at least one example,interaction module 248 can receive a communication from merchantcomputing device(s) 202. For example, a communication can includecontent such as a recommendation, an announcement, a question, anadvertisement, etc. Examples of the type(s) of communication are (1) adirect message to another member of the merchant group, (2) a post to amessage board or other internet forum associated with the merchantgroup, (3) a message in a group chat with other members of the merchantgroup, and/or (4) a request to browse or search the merchant groupmessage board content, etc. A merchant can be associated with (or made amember of) a merchant group by a grouping module 246 of the servicecomputing device(s) 204, as described above in relation to FIG. 4 .

Block 504 illustrates determining the identity of the merchant who sentthe communication. For instance, interaction module 248 can determinethe merchant who sent the communication based at least in part onmetadata associated with the communication having an indicator ofidentity of the merchant who sent the communication. In at least oneexample, the indicator can be a merchant identifier, a merchantcomputing device address, etc.

Block 506 illustrates determining a communication type associated withthe communication. In at least one example, interaction module 248 candetermine the communication type a merchant intends to use (e.g., textmessage, email, chat message, group chat message, post to message board,search query of message board, etc.) based at least in part on data ormetadata associated with the communication having an indicator orcommunication type. In another example, interaction module 248 candetermine the communication type to use when the sender does not specifywhich communication type is intended and/or requests assistance ofpayment processing service to determine the communication type. Forexample, the interaction module may determine that the optimumcommunication channel for the recommended merchant at a particular time(during working hours) is through the merchant POS device, while duringthe evening the best means of communication is via email or textmessage.

Block 508 illustrates determining intended recipient(s) associated withthe communication. For the purpose of this discussion, an intendedrecipient can be an individual merchant and/or merchant group. In atleast one example, interaction module 248 can determine whether thecommunication is directed to individual merchant(s) and/or merchantgroup(s) based at least in part on the communication type.

In some examples, membership in the social network for merchantsdescribed herein can enable a merchant to send a communication toindividual merchant(s) in merchant group(s) to which the merchantbelongs. For instance, the merchant can send a direct message to anindividual merchant that is associated with a same merchant group as themerchant. In such examples, interaction module 248 can determine theintended recipient(s) of the communication based at least in part on thecommunication type (e.g., email, text, etc.) and/or fields of thecommunication (e.g., “to,” addressee, etc.).

In other examples, the merchant can send a communication that isdirected to each member of a merchant group to which the merchantbelongs. For instance, the merchant can post to a message boardassociated with the merchant group. In an example, interaction module248 can determine that the communication type is a type intended for amerchant group (e.g., a post to a message board, a group chat, etc.). Insome examples, interaction module 248 can leverage the identity of themerchant to determine with which merchant group(s) the merchant isassociated. For instance, interaction module 248 can determine therelevant merchant group(s) of the merchant based on the merchantgroup(s) with which the merchant is associated. In some examples, absentany indication from the merchant, interaction module 248 can determinethat all merchant group(s) with which the merchant is associated are theintended recipient(s).

In other examples, the communication can be directed to a subset of theone or more merchant groups. In at least one example, the merchant canspecify one or more merchant groups that are the intended recipient(s)of the communication. In such an example, interaction module 248 candetermine the relevant merchant group(s) based at least in part on (1)metadata associated with the communication having an indicator of themerchant group(s) from which the merchant is sending the communication(e.g., an email template generated when the merchant was active on themessage board for a particular merchant group), (2) a selection by themerchant of a control of UI 217 indicating the relevant merchant group,and/or (3) entry of the merchant group by the merchant into a text fieldof UI 217.

In another example, determining intended recipient(s) associated withthe communication comprises determining a recipient when the recipientmerchant or merchant group is unknown. For instance interaction module248 can determine an intended recipient based on a search ofcommunication records, for example, for the relevant merchant group(s).That is, interaction module 248 can identify an intended recipient basedon previous communication records and can recommend an intendedrecipient. In at least one example, an intended recipient can be thesupport team. FIG. 6 , described below, illustrates an example processfor determining a recommended merchant recipient responsive to receivingan inquiry that is not directed to any particular merchant and can lacka particular intended recipient. In that example, interaction module 248determines a recommended merchant recipient to which to direct theinquiry by, for instance, accessing merchant information 254 associatedwith the inquiring merchant and the plurality of other merchantsassociated with the merchant group(s), analyzing similarity between theinquiring merchant and the plurality of other merchants, and identify arecommended merchant recipient to whom to direct the inquiry.

Block 510 illustrates determining whether the communication ispermitted. In some examples, interaction module 248 can validate thatthe merchant is permitted to communicate with the intended merchant(s)and/or merchant group(s). For instance, in at least one example,interaction module 248 can access a merchant profile associated with themerchant to determine any restrictions on merchant interactions withother members of the merchant group(s) or the payment processingservice. If the merchant is permitted to communicate with the intendedmerchant(s) and/or merchant group(s), interaction module 248 can causethe communication to be presented to the intended recipient(s), asillustrated in block 512. In at least one example, interaction module248 can route the communication to the intended recipient(s) (e.g.,merchant computing devices operated by the intended recipient(s)) andcan cause the communication to be presented to the intendedrecipient(s).

In at least one example the communication can be a direct message (e.g.,text message, email, chat message, etc.) and interaction module 248 cantransmit the direct message to one or more of the intended recipient(s).Interaction module 248 can transmit the direct message to the merchantcomputing device(s) of the intended recipient(s) and/or the directmessage can be surfaced to the intended recipient(s) through a websiteassociated with payment processing service (e.g., via UI for socialnetwork access 217). Additionally, in at least one example, interactionmodule 248 can transmit a message to the merchant who sent thecommunication indicating that the email has been transmitted to theintended recipient(s).

In another example, the communication can be a post to a message boardof a merchant group. Interaction module 248 can cause the post to bepresented via the message board and can send a notification to membersof the particular merchant group indicating that a new post has beenadded to the message board. In at least one example, the message boardcan be accessible via UI for social network access 217. Additionally, inat least one example, interaction module 248 can transmit a message tothe merchant who sent the communication indicating that the post hasbeen posted to the message board.

In another example, the communication can be a message intended to bedisplayed in a group chat. Interaction module 248 can cause presentationof the communication either on merchant computing device(s) 202associated with the recommended or intended recipient(s) and/or on awebpage associated with the payment processing service (e.g., via UI forsocial network access 217).

In another example, the communication can be a search query that amerchant would like to implement on a message board. Interaction module248 can execute the query on the message board content, for instance, oron other social network content for which the merchant is authorized byservice computing device(s) 204 to access. Interaction module 248 cancause presentation of the search results to the merchant who made thesearch query, either on merchant computing device(s) 202 associated withthe merchant and/or on a webpage associated with the payment processingservice (e.g., via UI for social network access 217).

If the merchant is not permitted to communicate with the intendedmerchant(s) and/or merchant group(s), interaction module 248 can rejectthe communication and can notify the merchant that the communication isnot permitted, as illustrated in block 514. That is, interaction module248 can send an indication to merchant computing device(s) 202 notifyingthe merchant that the communication failed (e.g., via UI for socialnetwork access 217).

FIG. 6 is a flow diagram illustrating an example process 600 determininga recommended merchant recipient to answer a merchant inquiry. FIG. 6 isdescribed in the context of the environment and/or device(s) describedabove with reference to FIG. 2 , but is not limited to such environmentand/or device(s).

Block 602 illustrates receiving an inquiry from merchant computingdevice(s) associated with an inquiring merchant. In at least oneexample, interaction module 248 can receive the inquiry from merchantcomputing device(s) 202. The inquiry can include a question. Examples ofthe type(s) of inquiry can include (1) a question about operating amerchant computing device, (2) a question specific to thecharacteristics of the inquiring merchant (e.g., location, merchanttype, inventory, etc.), etc.

Block 604 illustrates determining whether the inquiring merchant isalready associated with a merchant group. In some examples, interactionmodule 248 can validate that the merchant is a member of any merchantgroup(s). For instance, in at least one example, interaction module 248can access a merchant profile associated with the merchant to determinemembership in merchant group(s). Interaction module 248 can determine,from the merchant profile(s), if the merchant has an indicatorindicating membership in a merchant group. Interaction module 248 canalso determine from the merchant profile(s) if there are mappings orother associations between the merchant and a merchant group.

Block 606 illustrates associating the inquiring merchant with merchantgroup(s) if the merchant is not already associated with a merchantgroup. For example, a merchant can be associated with (or made a memberof) a merchant group by a grouping module 246 of the service computingdevice(s) 204, as described above in relation to FIG. 4 .

Block 608 illustrates, based at least in part on the inquiring member isdetermined to be associated with merchant group(s) or once the inquiringmember is associated with merchant group(s), determining a recommendedmerchant recipient to which to direct the inquiry. Interaction module248 can access merchant information 254 associated with the inquiringmerchant and the plurality of other merchants associated with themerchant group(s). Interaction module 248 can leverage data model(s) 252to analyze merchant information 254 of the inquiring merchant and theplurality of other merchants. Data model(s) 252 can output similarityscores representative of a similarity between the inquiring merchant andeach of the plurality of other merchants. Interaction module 248 cancompare the similarity scores and identify (e.g., by ranking thesimilarity scores and identifying the top-ranked merchant) a recommendedmerchant recipient to whom to direct the inquiry.

Additionally, or alternatively, interaction module 248 can determine arecommended merchant recipient to answer the question by analyzingprevious communications from, to, between, and/or among the plurality ofmerchants associated with the merchant group(s). Based on the questionand the previous communications, interaction module 248 can identify atleast one recommended merchant recipient of the plurality of merchants.

Block 610 illustrates sending the inquiry of the inquiring merchant tothe recommended merchant recipient. In one example, payment processingservice can cause the inquiry to be sent to a merchant computing deviceof the recommended merchant recipient to be presented on merchantcomputing device of the recommended merchant recipient. In an additionaland/or alternative example, the inquiry can be surfaced to therecommended merchant recipient through a website associated with paymentprocessing service.

Block 612 illustrates payment processing service facilitating ongoingcommunications between the inquiring merchant and the recommendedrecipient. In one example, interaction module 246 can provision themerchant social network to enable communication by enabling a directcommunication channel between the inquiring merchant and the recommendedrecipient and/or by facilitating access by the direct communicationchannel to a merchant computing device of the recommended recipient.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described. Rather,the specific features and acts are disclosed as example forms ofimplementing the claims.

What is claimed is:
 1. A method comprising: receiving, by a paymentprocessing service and from an instance of a merchant applicationexecuting on a merchant device of a merchant, transaction data of atransaction performed between the merchant and one or more customers,wherein the instance of the merchant application is provided by thepayment processing service for configuring the merchant device as apoint-of-sale (POS) terminal to communicate the transaction data over anetwork to the payment processing service; processing, by the paymentprocessing service, a payment associated with the transaction based atleast in part on the transaction data; determining, by the paymentprocessing service, and based on analyzing at least the transaction datawith a data model, a shared characteristic associated with the merchantand a merchant group; associating, by the payment processing service,the merchant with the merchant group; provisioning, by the paymentprocessing service, a merchant social network based on the merchantgroup, wherein the merchant social network provides the instance of themerchant application with to access one or more communication serviceswithin the merchant group; and based at least in part on receiving acommunication from the merchant, activating, by the payment processingservice, the one or more communication services between the merchant andthe merchant group via the merchant social network, wherein the one ormore communication services enable near real-time communications betweenthe merchant and another merchant included in the merchant group.
 2. Themethod of claim 1, wherein the communication is associated with asupport request, the method further comprising; identifying, by thepayment processing service, information regarding the support request,wherein the information is associated with the merchant group; andtransmitting, by the payment processing service to a device operated byanother merchant of the merchant group, the information regarding thecommunication associated with the support request.
 3. The method ofclaim 1, further comprising: receiving, by the payment processingservice and from the instance of the merchant application, a message forthe merchant group; presenting, by the payment processing service, themessage via an electronic message board, wherein the presenting is basedat least in part on the merchant being included in the merchant group;and notifying, by the payment processing service, at least the othermerchant included in the merchant group that the message has beenpresented.
 4. The method of claim 1, further comprising transmitting, bythe payment processing service and to individual devices operated byrespective members of the merchant group, a message concerning a topicrelevant to the merchant group.
 5. The method of claim 1, wherein theshared characteristic excludes location.
 6. The method of claim 1,wherein the shared characteristic is further based on other data storedby the payment processing service, the other data comprising dataprovided by at least one of: at least one merchant, at least onethird-party information source, or at least one support service record.7. A system associated with a payment processing service, the systemcomprising: one or more processors; and one or more computer-readablemedia storing instructions executable by the one or more processors,wherein the instructions program the one or more processors to: receive,by the payment processing service and from an instance of a merchantapplication executing on a merchant device associated with a merchant ofa plurality of merchants, transaction data of a transaction performedbetween the merchant and one or more customers, wherein the instance ofthe merchant application is provided by the payment processing servicefor configuring the merchant device as a point-of-sale (POS) terminal tocommunicate the transaction data over a network to the paymentprocessing service; process, by the payment processing service, apayment for the transaction based at least in part on the transactiondata; determine, by the payment processing service, and based onanalyzing at least the transaction data with a data model, a similaritybetween the merchant and a merchant group; associate, by the paymentprocessing service, the merchant with the merchant group; provision, bythe payment processing service and based at least on the merchant group,a merchant social network, wherein the merchant social network providesthe instance of the merchant application with access to one or morecommunication services for communications within the merchant group; andbased at least in part on receiving a communication from the merchant,activate, by the payment processing service and via the merchant socialnetwork, wherein the one or more communication services enable nearreal-time communications between the merchant and another merchantincluded in the merchant group.
 8. The system of claim 7, wherein acommunication service of the one or more communication services isdirect messaging.
 9. The system of claim 7, wherein a communicationservice of the one or more communication services is posting to amessage board associated with the merchant group.
 10. The system ofclaim 7, wherein associating the merchant with the merchant groupcomprises automatically adding the merchant to the merchant groupwithout receiving input from at least one of an agent associated withthe payment processing service or the merchant.
 11. The system of claim7, wherein associating the merchant with the merchant group comprises:presenting, by the payment processing service, an option to join themerchant group via at least one of the merchant device or a websiteassociated with the payment processing service; receiving, by thepayment processing service, an indication of an election by the merchantto join the merchant group; and adding, by the payment processingservice, the merchant to the merchant group.
 12. The system of claim 7,wherein, prior to analyzing the transaction data with the data model,the instructions further program the one or more processors to: access,by the payment processing service, merchant information associated withthe plurality of merchants, groupings of such merchants, and similarityscores previously determined for such merchants; and train, by thepayment processing service, the data model using at least one machinelearning mechanism, the data model configured to output indications ofsimilarity between individual merchants of the plurality of merchants.13. One or more non-transitory computer-readable media storinginstructions executable by one or more processors, wherein theinstructions program the one or more processors to: receive, by apayment processing service and from an instance of a merchantapplication executing on a merchant device of a merchant, transactiondata of a transaction performed between the merchant and one or morecustomers, wherein the instance of the merchant application is providedby the payment processing service for configuring the merchant device asa point-of-sale (POS) terminal to communicate the transaction data overa network to the payment processing service; process, by the paymentprocessing service, a payment associated with the transaction based atleast in part on the transaction data; determine, by the paymentprocessing service, and based on analyzing at least the transaction datawith a data model, a shared characteristic associated with the merchantand a merchant group; associate, by the payment processing service, themerchant with the merchant group; provision, by the payment processingservice, a merchant social network based on the merchant group, whereinthe merchant social network provides the instance of the merchantapplication with access to one or more communication services within themerchant group; and based at least in part on receiving a communicationfrom the merchant, activate, by the payment processing service, the oneor more communication services between the merchant and the merchantgroup via the merchant social network, wherein the one or morecommunication services enable near real-time communications between themerchant and another merchant included in the merchant group.
 14. Theone or more non-transitory computer-readable media of claim 13, whereinassociating the merchant with the merchant group is based at least inpart on a similarity score meeting or exceeding a threshold, wherein thesimilarity score is based at least in part on the shared characteristic.15. The one or more non-transitory computer-readable media of claim 13,wherein activating the one or more communication services comprises atleast one of activating communications between the merchant and at leastone other member of the merchant group or activating access by themerchant to information posted to an internet forum by other members ofthe merchant group.
 16. The one or more non-transitory computer-readablemedia of claim 15, wherein the communications comprise at least one ofnear real-time text communication or email communication.
 17. The one ormore non-transitory computer-readable media of claim 13, wherein theinstructions further program the one or more processors to provide, bythe payment processing service, an incentive to a member of the merchantgroup based at least in part on the member answering at least onecommunication from another member of the merchant group.
 18. The one ormore non-transitory computer-readable media of claim 13, wherein theinstructions further program the one or more processors to: receive, bythe payment processing service and from the instance of the merchantapplication executing on the merchant device, the communication, whereinthe question is associated with a support request; identify, by thepayment processing service, information regarding the support request,wherein the information is associated with the merchant group; andtransmit, by the payment processing service to a device operated by theother merchant of the merchant group, the information regarding thecommunication associated with the support request.
 19. The one or morenon-transitory computer-readable media of claim 18, wherein identifyingthe information regarding the communication associated with the supportrequest comprises performing natural language processing of pastcommunications between one or more merchants of the merchant group andthe payment processing service, or text-searching electronic notes ofsupport agents associated with the payment processing service.
 20. Theone or more non-transitory computer-readable media of claim 13, wherein,prior to analyzing the transaction data with the data model, theinstructions further program the one or more processors to: access, bythe payment processing service, training data including transaction dataand merchant information associated with a plurality of merchants, oneor more merchant groups associated with the plurality of merchants, andsimilarity scores determined for the plurality of merchants; and train,by the payment processing service, the data model using at least onemachine learning mechanism and the training data.